Devices and Vaccines

An On-Demand Neuromorphic Vision System Enabled by a Multi-Paradigm Neuromorphic Device and Hierarchical Reconfigurability Designed from Device to System Level.

There are two general approaches in guiding intelligent vision system development: one emphasizes ultra-flexibility (reconfigurability) for adapting to various scenarios, and the other emphasizes ultrahigh power efficiency tailored to specific applications. The pinnacle design is geared toward the biological vision system with concurrent high levels of on-demand intelligence, efficiency, and flexi...

Machine learning-assisted wearable SERS-microfluidic system for rapid detection of sweat biomarkers and stimulants.

Sweat is an ideal biofluid for noninvasive monitoring of athletes' physiological status during exercise, as its rich chemical composition directly reflects health and metabolic state. Herein, we develop a wearable device based on segmented circular microfluidic paper-based surface-enhanced Raman scattering (SCMP-SERS) for real-time sweat analysis during physical activity. The core sensor incorpora...

Personalized Diabetes Treatment Support Using Large Language Models Fine-Tuned on Electronic Health Records: Development and Evaluation Study.

BACKGROUND: Effective diabetes management requires individualized treatment strategies tailored to patients' clinical characteristics. With recent adv...

Chiropto-Neuromorphic Devices Based on a Photocatalytic Dye/Polymer Semiconductor Bulk Heterojunction for Circularly Polarized Light Detection and Memorization.

Neuromorphic computing, which emulates the energy-efficient processing of the human brain, has emerged as a key technology for next-generation artific...

AI-driven 3D virtual surgical planning in total hip arthroplasty: a machine learning approach for precision implant positioning and improved clinical outcomes.

PURPOSE: To explore the clinical significance of the artificial intelligence (AI)-assisted three-dimensional (3D) planning system AI-HIP in total hip ...

Machine learning model predicts prognosis in SARS-CoV-2-infected autoimmune encephalitis patients.

OBJECTIVE: To assess the neurological prognosis of patients with autoimmune encephalitis (AE) after severe acute respiratory syndrome coronavirus 2 (S...

Simultaneous Segmentation of Geographic Atrophy in Longitudinally Acquired Fundus Autofluorescence Images.

PURPOSE: Accurately measuring geographic atrophy (GA) progression in clinical trials is challenging, owing to its slow and variable nature. This study...

Deep Learning Artificial Intelligence and Restriction Spectrum Imaging for Patient-level Detection of Clinically Significant Prostate Cancer on Biparametric Magnetic Resonance Imaging.

BACKGROUND AND OBJECTIVE: Our aim was to evaluate whether combining the maximum restriction score derived from restriction spectrum imaging (RSIrsmax)...

Comparison of Artificial Intelligence Models for Automatic Segmentation of the Mandibular Canals and Branches.

OBJECTIVES: This study aimed to compare and improve the performance of three deep learning models, i.e., U-Net Transformer (UNETR), Swin UNETR, and 3D...

Screening for Tumor Microtube-Targeting Drugs Identifies PKC Modulators as Multipotent Inhibitors of Glioblastoma Progression.

UNLABELLED: Glioblastomas are incurable primary brain tumors that depend on neural-like cellular processes, tumor microtubes (TM), to invade the brain...

Nanoparticle approaches for hepatitis therapy and clinical translation.

BACKGROUND: Hepatitis B and C viruses (HBV and HCV) remain major global health challenges, contributing significantly to liver-related morbidity and m...

Advancing Psychiatric Safety With the Predictive Risk Identification for Mental Health Events Tool: Retrospective Cohort Study.

BACKGROUND: Patient safety incidents are a leading cause of harm in psychiatric settings, yet early warning systems (EWS) tailored to mental health re...

Knowledge, Awareness and Perception of Artificial Intelligence (AI) - driven Prosthodontics in Jordan: A Cross-sectional Study.

PURPOSE: Artificial intelligence (AI) is transforming modern dentistry, particularly in prosthodontics. However, evidence regarding AI integration amo...

Clinical-Radiomics hybrid prediction of the Risks of pedicle screw loosening after posterior lumbar fusion.

OBJECTIVE: We aimed to construct a risk prediction model for PSL after posterior lumbar fusion using machine learning and radiomic methods. SUMMARY OF...

A fast fully automated approach for evaluating calcified lesions in intravascular ultrasound.

AIMS: Catheter-based coronary intervention is an effective treatment for acute coronary syndrome. However, calcified plaques pose significant challeng...

Coupling Data-Driven and Reinforcement Learning for Material Development and Device Management in Batteries.

The growing demand for high-energy, safe, and durable batteries demands innovative strategies in both material discovery and device management. Conven...

A Multimodal Model for Caries Screening Using Intraoral Images and Questionnaires.

INTRODUCTION AND AIMS: To develop a multimodal deep learning model for dental caries screening in children by integrating intraoral photographs and qu...

Molecular Biointerface Characterization for an Implanted Medical Device Using Cryogenic Orbitrap Secondary Ion Mass Spectrometry (Cryo-OrbiSIMS).

Implanted medical devices often fail due to foreign body reactions (FBRs), a process that is still not fully understood. This work presents a depth pr...

Scaling medical device regulatory science using large language models.

Advances in artificial intelligence (AI) and machine learning (ML) have led to a surge in AI/ML-enabled medical devices, posing new challenges for reg...

Variant calling in genomics: A comparative performance analysis and decision guide.

The accurate detection of genetic variants is critical for advancing genomics research and precision medicine. However, this task remains challenging ...